Senior Software Development Engineer

At GoDaddy the future of work looks different for each team. Some teams work in the office full-time; others have a hybrid arrangement (they work remotely some days and in the office some days) and some work entirely remotely.​

This is a remote position, so you’ll be working remotely from your home. You may occasionally visit a GoDaddy office to meet with your team for events or meetings.  

Help shape how engineers, analysts, and business teams build on and use our enterprise data platform. You'll design data products and the self-service experiences around them — from the data model to the APIs and workflows producers and consumers rely on — so teams can get what they need without waiting on tickets. You'll also help build the enterprise data context that lets people and AI find, understand, and trust data. This role suits a hands-on data engineer with strong data modeling, AWS, and Python skills who enjoys owning a problem from the user's need down to the data underneath.

• →Design data models and domain-driven building blocks that turn raw data into reusable, well-governed data products for end consumers
• →Contribute to the enterprise data context — semantic models, ontologies, and knowledge bases that make data discoverable and usable by people and AI agents
• →Build end-to-end self-service experiences for data producers and consumers, including onboarding, SQL automation, data quality monitoring, and the APIs and workflows that expose data products
• →Build and evolve AI-assisted and agentic automation that removes manual work, including migration support, impact assessment, and guided workflows for platform and data teams
• →Own incident response for the services you build: lead root-cause analysis and after-action reviews, ship durable fixes, and write runbooks so first-line support can resolve recurring issues on their own
• →Drive priorities for Platform UX services in partnership with engineering leadership and teams across US and India time zones: turn user needs into a prioritized backlog, weigh trade-offs, unblock users, and own the outcomes of what you deliver

• 7+ years in data engineering, data platform engineering, or software engineering
• Strong data modeling and data architecture skills, including domain-driven design and building reusable data products for downstream consumers
• 5+ years of professional Python, building APIs, automation, and data or platform tooling, with the ability to troubleshoot distributed data systems
• Building self-service data experiences — APIs, workflows, or tooling that let producers and consumers work independently
• Designing modular, reusable platform patterns — frameworks, plugins, or marketplaces — that scale automation across many teams
• Hands-on experience with AWS (S3, Lambda, Glue, Lake Formation, Redshift, API Gateway), lakehouse architectures and Apache Iceberg in production, and orchestration with Apache Airflo

• Production experience building agentic or AI-assisted workflows for analytics, migration, or platform enablement, including semantic layers, ontologies, or knowledge graphs/knowledge bases for enterprise data
• Experience with data quality frameworks, data governance, or access management

We encourage you to apply even if your experience or skillset doesn’t align perfectly with every requirement. We value a wide range of backgrounds and transferable skills, and we are excited to support learning and growth.